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README.md

@@ -0,0 +1,724 @@
+---
+language:
+- bg
+- bs_Latn
+- es
+- fr
+- hr
+- it
+- itc
+- mk
+- pt
+- sh
+- sl
+- sr_Cyrl
+- sr_Latn
+- zls
+
+tags:
+- translation
+- opus-mt-tc
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-zls-itc
+  results:
+  - task:
+      name: Translation bul-fra
+      type: translation
+      args: bul-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: bul fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 34.4
+       - name: chr-F
+         type: chrf
+         value: 0.60640
+  - task:
+      name: Translation bul-ita
+      type: translation
+      args: bul-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: bul ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 24.0
+       - name: chr-F
+         type: chrf
+         value: 0.54135
+  - task:
+      name: Translation bul-por
+      type: translation
+      args: bul-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: bul por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.4
+       - name: chr-F
+         type: chrf
+         value: 0.59322
+  - task:
+      name: Translation bul-ron
+      type: translation
+      args: bul-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: bul ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 27.1
+       - name: chr-F
+         type: chrf
+         value: 0.55558
+  - task:
+      name: Translation bul-spa
+      type: translation
+      args: bul-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: bul spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.4
+       - name: chr-F
+         type: chrf
+         value: 0.50962
+  - task:
+      name: Translation hrv-fra
+      type: translation
+      args: hrv-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: hrv fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 33.1
+       - name: chr-F
+         type: chrf
+         value: 0.59349
+  - task:
+      name: Translation hrv-ita
+      type: translation
+      args: hrv-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: hrv ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.5
+       - name: chr-F
+         type: chrf
+         value: 0.52980
+  - task:
+      name: Translation hrv-por
+      type: translation
+      args: hrv-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: hrv por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 30.2
+       - name: chr-F
+         type: chrf
+         value: 0.57402
+  - task:
+      name: Translation hrv-ron
+      type: translation
+      args: hrv-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: hrv ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.9
+       - name: chr-F
+         type: chrf
+         value: 0.53650
+  - task:
+      name: Translation hrv-spa
+      type: translation
+      args: hrv-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: hrv spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.5
+       - name: chr-F
+         type: chrf
+         value: 0.50161
+  - task:
+      name: Translation mkd-fra
+      type: translation
+      args: mkd-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: mkd fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 35.2
+       - name: chr-F
+         type: chrf
+         value: 0.60801
+  - task:
+      name: Translation mkd-ita
+      type: translation
+      args: mkd-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: mkd ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.9
+       - name: chr-F
+         type: chrf
+         value: 0.53543
+  - task:
+      name: Translation mkd-por
+      type: translation
+      args: mkd-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: mkd por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 33.9
+       - name: chr-F
+         type: chrf
+         value: 0.59648
+  - task:
+      name: Translation mkd-ron
+      type: translation
+      args: mkd-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: mkd ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.0
+       - name: chr-F
+         type: chrf
+         value: 0.54998
+  - task:
+      name: Translation mkd-spa
+      type: translation
+      args: mkd-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: mkd spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.8
+       - name: chr-F
+         type: chrf
+         value: 0.51079
+  - task:
+      name: Translation slv-fra
+      type: translation
+      args: slv-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: slv fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.5
+       - name: chr-F
+         type: chrf
+         value: 0.58233
+  - task:
+      name: Translation slv-ita
+      type: translation
+      args: slv-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: slv ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.4
+       - name: chr-F
+         type: chrf
+         value: 0.52390
+  - task:
+      name: Translation slv-por
+      type: translation
+      args: slv-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: slv por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 29.0
+       - name: chr-F
+         type: chrf
+         value: 0.56436
+  - task:
+      name: Translation slv-ron
+      type: translation
+      args: slv-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: slv ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 25.0
+       - name: chr-F
+         type: chrf
+         value: 0.53116
+  - task:
+      name: Translation slv-spa
+      type: translation
+      args: slv-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: slv spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 21.1
+       - name: chr-F
+         type: chrf
+         value: 0.49621
+  - task:
+      name: Translation srp_Cyrl-fra
+      type: translation
+      args: srp_Cyrl-fra
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: srp_Cyrl fra devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 36.0
+       - name: chr-F
+         type: chrf
+         value: 0.62110
+  - task:
+      name: Translation srp_Cyrl-ita
+      type: translation
+      args: srp_Cyrl-ita
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: srp_Cyrl ita devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 23.9
+       - name: chr-F
+         type: chrf
+         value: 0.54083
+  - task:
+      name: Translation srp_Cyrl-por
+      type: translation
+      args: srp_Cyrl-por
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: srp_Cyrl por devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 34.9
+       - name: chr-F
+         type: chrf
+         value: 0.61248
+  - task:
+      name: Translation srp_Cyrl-ron
+      type: translation
+      args: srp_Cyrl-ron
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: srp_Cyrl ron devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.8
+       - name: chr-F
+         type: chrf
+         value: 0.56235
+  - task:
+      name: Translation srp_Cyrl-spa
+      type: translation
+      args: srp_Cyrl-spa
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: srp_Cyrl spa devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 22.8
+       - name: chr-F
+         type: chrf
+         value: 0.51698
+  - task:
+      name: Translation bul-fra
+      type: translation
+      args: bul-fra
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: bul-fra
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 52.9
+       - name: chr-F
+         type: chrf
+         value: 0.68971
+  - task:
+      name: Translation bul-ita
+      type: translation
+      args: bul-ita
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: bul-ita
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 45.1
+       - name: chr-F
+         type: chrf
+         value: 0.66412
+  - task:
+      name: Translation bul-spa
+      type: translation
+      args: bul-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: bul-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 49.7
+       - name: chr-F
+         type: chrf
+         value: 0.66672
+  - task:
+      name: Translation hbs-fra
+      type: translation
+      args: hbs-fra
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: hbs-fra
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 48.1
+       - name: chr-F
+         type: chrf
+         value: 0.66434
+  - task:
+      name: Translation hbs-ita
+      type: translation
+      args: hbs-ita
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: hbs-ita
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 53.5
+       - name: chr-F
+         type: chrf
+         value: 0.72381
+  - task:
+      name: Translation hbs-spa
+      type: translation
+      args: hbs-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: hbs-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 58.0
+       - name: chr-F
+         type: chrf
+         value: 0.73105
+  - task:
+      name: Translation hrv-fra
+      type: translation
+      args: hrv-fra
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: hrv-fra
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 44.3
+       - name: chr-F
+         type: chrf
+         value: 0.62800
+  - task:
+      name: Translation hrv-spa
+      type: translation
+      args: hrv-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: hrv-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 57.5
+       - name: chr-F
+         type: chrf
+         value: 0.71370
+  - task:
+      name: Translation mkd-spa
+      type: translation
+      args: mkd-spa
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: mkd-spa
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 62.1
+       - name: chr-F
+         type: chrf
+         value: 0.75366
+  - task:
+      name: Translation srp_Latn-ita
+      type: translation
+      args: srp_Latn-ita
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: srp_Latn-ita
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 59.6
+       - name: chr-F
+         type: chrf
+         value: 0.76045
+---
+# opus-mt-tc-big-zls-itc
+
+## Table of Contents
+- [Model Details](#model-details)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+- [Training](#training)
+- [Evaluation](#evaluation)
+- [Citation Information](#citation-information)
+- [Acknowledgements](#acknowledgements)
+
+## Model Details
+
+Neural machine translation model for translating from South Slavic languages (zls) to Italic languages (itc).
+
+This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
+**Model Description:**
+- **Developed by:** Language Technology Research Group at the University of Helsinki
+- **Model Type:** Translation (transformer-big)
+- **Release**: 2022-08-10
+- **License:** CC-BY-4.0
+- **Language(s):**  
+  - Source Language(s): bos_Latn bul hbs hrv mkd slv srp_Cyrl srp_Latn
+  - Target Language(s): fra ita por spa
+  - Valid Target Language Labels: >>fra<< >>ita<< >>por<< >>spa<<
+- **Original Model**: [opusTCv20210807_transformer-big_2022-08-10.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/zls-itc/opusTCv20210807_transformer-big_2022-08-10.zip)
+- **Resources for more information:**
+  - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+  - More information about released models for this language pair: [OPUS-MT zls-itc README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zls-itc/README.md)
+  - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
+  - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/
+
+This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>fra<<`
+
+## Uses
+
+This model can be used for translation and text-to-text generation.
+
+## Risks, Limitations and Biases
+
+**CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.**
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
+
+## How to Get Started With the Model
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>fra<< Dobar dan, kako si?",
+    ">>spa<< Znam da je ovo čudno."
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-zls-itc"
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
+
+for t in translated:
+    print( tokenizer.decode(t, skip_special_tokens=True) )
+
+# expected output:
+#     Bonjour, comment allez-vous ?
+#     Sé que esto es raro.
+```
+
+You can also use OPUS-MT models with the transformers pipelines, for example:
+
+```python
+from transformers import pipeline
+pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-zls-itc")
+print(pipe(">>fra<< Dobar dan, kako si?"))
+
+# expected output: Bonjour, comment allez-vous ?
+```
+
+## Training
+
+- **Data**: opusTCv20210807 ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+- **Pre-processing**: SentencePiece (spm32k,spm32k)
+- **Model Type:**  transformer-big
+- **Original MarianNMT Model**: [opusTCv20210807_transformer-big_2022-08-10.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/zls-itc/opusTCv20210807_transformer-big_2022-08-10.zip)
+- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+
+## Evaluation
+
+* test set translations: [opusTCv20210807_transformer-big_2022-08-10.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zls-itc/opusTCv20210807_transformer-big_2022-08-10.test.txt)
+* test set scores: [opusTCv20210807_transformer-big_2022-08-10.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/zls-itc/opusTCv20210807_transformer-big_2022-08-10.eval.txt)
+* benchmark results: [benchmark_results.txt](benchmark_results.txt)
+* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
+
+| langpair | testset | chr-F | BLEU  | #sent | #words |
+|----------|---------|-------|-------|-------|--------|
+| bul-fra | tatoeba-test-v2021-08-07 | 0.68971 | 52.9 | 446 | 3669 |
+| bul-ita | tatoeba-test-v2021-08-07 | 0.66412 | 45.1 | 2500 | 16951 |
+| bul-spa | tatoeba-test-v2021-08-07 | 0.66672 | 49.7 | 286 | 1783 |
+| hbs-fra | tatoeba-test-v2021-08-07 | 0.66434 | 48.1 | 474 | 3370 |
+| hbs-ita | tatoeba-test-v2021-08-07 | 0.72381 | 53.5 | 534 | 3208 |
+| hbs-spa | tatoeba-test-v2021-08-07 | 0.73105 | 58.0 | 607 | 3766 |
+| hrv-fra | tatoeba-test-v2021-08-07 | 0.62800 | 44.3 | 258 | 1943 |
+| hrv-spa | tatoeba-test-v2021-08-07 | 0.71370 | 57.5 | 254 | 1702 |
+| mkd-spa | tatoeba-test-v2021-08-07 | 0.75366 | 62.1 | 217 | 1121 |
+| srp_Latn-ita | tatoeba-test-v2021-08-07 | 0.76045 | 59.6 | 212 | 1292 |
+| bul-fra | flores101-devtest | 0.60640 | 34.4 | 1012 | 28343 |
+| bul-ita | flores101-devtest | 0.54135 | 24.0 | 1012 | 27306 |
+| bul-por | flores101-devtest | 0.59322 | 32.4 | 1012 | 26519 |
+| bul-ron | flores101-devtest | 0.55558 | 27.1 | 1012 | 26799 |
+| bul-spa | flores101-devtest | 0.50962 | 22.4 | 1012 | 29199 |
+| hrv-fra | flores101-devtest | 0.59349 | 33.1 | 1012 | 28343 |
+| hrv-ita | flores101-devtest | 0.52980 | 23.5 | 1012 | 27306 |
+| hrv-por | flores101-devtest | 0.57402 | 30.2 | 1012 | 26519 |
+| hrv-ron | flores101-devtest | 0.53650 | 25.9 | 1012 | 26799 |
+| hrv-spa | flores101-devtest | 0.50161 | 21.5 | 1012 | 29199 |
+| mkd-fra | flores101-devtest | 0.60801 | 35.2 | 1012 | 28343 |
+| mkd-ita | flores101-devtest | 0.53543 | 23.9 | 1012 | 27306 |
+| mkd-por | flores101-devtest | 0.59648 | 33.9 | 1012 | 26519 |
+| mkd-ron | flores101-devtest | 0.54998 | 28.0 | 1012 | 26799 |
+| mkd-spa | flores101-devtest | 0.51079 | 22.8 | 1012 | 29199 |
+| slv-fra | flores101-devtest | 0.58233 | 31.5 | 1012 | 28343 |
+| slv-ita | flores101-devtest | 0.52390 | 22.4 | 1012 | 27306 |
+| slv-por | flores101-devtest | 0.56436 | 29.0 | 1012 | 26519 |
+| slv-ron | flores101-devtest | 0.53116 | 25.0 | 1012 | 26799 |
+| slv-spa | flores101-devtest | 0.49621 | 21.1 | 1012 | 29199 |
+| srp_Cyrl-fra | flores101-devtest | 0.62110 | 36.0 | 1012 | 28343 |
+| srp_Cyrl-ita | flores101-devtest | 0.54083 | 23.9 | 1012 | 27306 |
+| srp_Cyrl-por | flores101-devtest | 0.61248 | 34.9 | 1012 | 26519 |
+| srp_Cyrl-ron | flores101-devtest | 0.56235 | 28.8 | 1012 | 26799 |
+| srp_Cyrl-spa | flores101-devtest | 0.51698 | 22.8 | 1012 | 29199 |
+
+## Citation Information
+
+* Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
+
+```
+@inproceedings{tiedemann-thottingal-2020-opus,
+    title = "{OPUS}-{MT} {--} Building open translation services for the World",
+    author = {Tiedemann, J{\"o}rg  and Thottingal, Santhosh},
+    booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Lisboa, Portugal",
+    publisher = "European Association for Machine Translation",
+    url = "https://aclanthology.org/2020.eamt-1.61",
+    pages = "479--480",
+}
+
+@inproceedings{tiedemann-2020-tatoeba,
+    title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
+    author = {Tiedemann, J{\"o}rg},
+    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.wmt-1.139",
+    pages = "1174--1182",
+}
+```
+
+## Acknowledgements
+
+The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
+
+## Model conversion info
+
+* transformers version: 4.16.2
+* OPUS-MT git hash: 8b9f0b0
+* port time: Fri Aug 12 13:57:47 EEST 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

@@ -0,0 +1,74 @@
+bul-fra	flores101-dev	0.60515	34.0	997	26706
+bul-ita	flores101-dev	0.53356	22.8	997	25840
+bul-por	flores101-dev	0.58413	31.3	997	25287
+bul-ron	flores101-dev	0.55870	27.9	997	25616
+bul-spa	flores101-dev	0.50507	22.2	997	27793
+hrv-fra	flores101-dev	0.59160	32.9	997	26706
+hrv-ita	flores101-dev	0.52624	22.6	997	25840
+hrv-por	flores101-dev	0.56567	29.7	997	25287
+hrv-ron	flores101-dev	0.53565	26.0	997	25616
+hrv-spa	flores101-dev	0.49356	21.2	997	27793
+mkd-fra	flores101-dev	0.60379	34.6	997	26706
+mkd-ita	flores101-dev	0.53334	23.5	997	25840
+mkd-por	flores101-dev	0.59103	32.9	997	25287
+mkd-ron	flores101-dev	0.55096	28.2	997	25616
+mkd-spa	flores101-dev	0.50218	22.3	997	27793
+slv-fra	flores101-dev	0.57857	31.1	997	26706
+slv-ita	flores101-dev	0.52418	22.2	997	25840
+slv-por	flores101-dev	0.55881	28.3	997	25287
+slv-ron	flores101-dev	0.53118	25.9	997	25616
+slv-spa	flores101-dev	0.49112	21.2	997	27793
+srp_Cyrl-fra	flores101-dev	0.62093	36.3	997	26706
+srp_Cyrl-ita	flores101-dev	0.53829	23.4	997	25840
+srp_Cyrl-por	flores101-dev	0.60678	34.7	997	25287
+srp_Cyrl-ron	flores101-dev	0.56395	29.0	997	25616
+srp_Cyrl-spa	flores101-dev	0.50659	22.1	997	27793
+bul-fra	flores101-devtest	0.60640	34.4	1012	28343
+bul-ita	flores101-devtest	0.54135	24.0	1012	27306
+bul-por	flores101-devtest	0.59322	32.4	1012	26519
+bul-ron	flores101-devtest	0.55558	27.1	1012	26799
+bul-spa	flores101-devtest	0.50962	22.4	1012	29199
+hrv-fra	flores101-devtest	0.59349	33.1	1012	28343
+hrv-ita	flores101-devtest	0.52980	23.5	1012	27306
+hrv-por	flores101-devtest	0.57402	30.2	1012	26519
+hrv-ron	flores101-devtest	0.53650	25.9	1012	26799
+hrv-spa	flores101-devtest	0.50161	21.5	1012	29199
+mkd-fra	flores101-devtest	0.60801	35.2	1012	28343
+mkd-ita	flores101-devtest	0.53543	23.9	1012	27306
+mkd-por	flores101-devtest	0.59648	33.9	1012	26519
+mkd-ron	flores101-devtest	0.54998	28.0	1012	26799
+mkd-spa	flores101-devtest	0.51079	22.8	1012	29199
+slv-fra	flores101-devtest	0.58233	31.5	1012	28343
+slv-ita	flores101-devtest	0.52390	22.4	1012	27306
+slv-por	flores101-devtest	0.56436	29.0	1012	26519
+slv-ron	flores101-devtest	0.53116	25.0	1012	26799
+slv-spa	flores101-devtest	0.49621	21.1	1012	29199
+srp_Cyrl-fra	flores101-devtest	0.62110	36.0	1012	28343
+srp_Cyrl-ita	flores101-devtest	0.54083	23.9	1012	27306
+srp_Cyrl-por	flores101-devtest	0.61248	34.9	1012	26519
+srp_Cyrl-ron	flores101-devtest	0.56235	28.8	1012	26799
+srp_Cyrl-spa	flores101-devtest	0.51698	22.8	1012	29199
+hbs-spa	tatoeba-test-v2020-07-28	0.73160	58.1	606	3762
+hrv-spa	tatoeba-test-v2020-07-28	0.71492	57.6	253	1698
+slv-fra	tatoeba-test-v2020-07-28	0.26482	10.3	442	3662
+bul-fra	tatoeba-test-v2021-03-30	0.68891	52.8	448	3689
+bul-spa	tatoeba-test-v2021-03-30	0.66812	49.8	288	1791
+hbs-fra	tatoeba-test-v2021-03-30	0.66430	48.0	479	3404
+hbs-ita	tatoeba-test-v2021-03-30	0.72403	53.4	537	3226
+hbs-spa	tatoeba-test-v2021-03-30	0.73080	58.1	615	3812
+hrv-fra	tatoeba-test-v2021-03-30	0.62774	44.1	261	1969
+hrv-spa	tatoeba-test-v2021-03-30	0.71268	57.4	261	1739
+mkd-spa	tatoeba-test-v2021-03-30	0.75405	62.1	223	1149
+slv-fra	tatoeba-test-v2021-03-30	0.26515	10.2	444	3673
+srp_Latn-ita	tatoeba-test-v2021-03-30	0.76034	59.5	213	1297
+bul-fra	tatoeba-test-v2021-08-07	0.68971	52.9	446	3669
+bul-ita	tatoeba-test-v2021-08-07	0.66412	45.1	2500	16951
+bul-spa	tatoeba-test-v2021-08-07	0.66672	49.7	286	1783
+hbs-fra	tatoeba-test-v2021-08-07	0.66434	48.1	474	3370
+hbs-ita	tatoeba-test-v2021-08-07	0.72381	53.5	534	3208
+hbs-spa	tatoeba-test-v2021-08-07	0.73105	58.0	607	3766
+hrv-fra	tatoeba-test-v2021-08-07	0.62800	44.3	258	1943
+hrv-spa	tatoeba-test-v2021-08-07	0.71370	57.5	254	1702
+mkd-spa	tatoeba-test-v2021-08-07	0.75366	62.1	217	1121
+slv-fra	tatoeba-test-v2021-08-07	0.26575	11.4	448	3792
+srp_Latn-ita	tatoeba-test-v2021-08-07	0.76045	59.6	212	1292

benchmark_translations.zip

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+size 9194324

config.json

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+  "activation_function": "relu",
+  "architectures": [
+    "MarianMTModel"
+  ],
+  "attention_dropout": 0.0,
+  "bad_words_ids": [
+    [
+      59412
+    ]
+  ],
+  "bos_token_id": 0,
+  "classifier_dropout": 0.0,
+  "d_model": 1024,
+  "decoder_attention_heads": 16,
+  "decoder_ffn_dim": 4096,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 6,
+  "decoder_start_token_id": 59412,
+  "decoder_vocab_size": 59413,
+  "dropout": 0.1,
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+  "encoder_ffn_dim": 4096,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 6,
+  "eos_token_id": 34288,
+  "forced_eos_token_id": 34288,
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "max_length": 512,
+  "max_position_embeddings": 1024,
+  "model_type": "marian",
+  "normalize_embedding": false,
+  "num_beams": 4,
+  "num_hidden_layers": 6,
+  "pad_token_id": 59412,
+  "scale_embedding": true,
+  "share_encoder_decoder_embeddings": true,
+  "static_position_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.18.0.dev0",
+  "use_cache": true,
+  "vocab_size": 59413
+}

pytorch_model.bin

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source.spm

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special_tokens_map.json

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+{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}

target.spm

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tokenizer_config.json

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+{"source_lang": "zls", "target_lang": "itc", "unk_token": "<unk>", "eos_token": "</s>", "pad_token": "<pad>", "model_max_length": 512, "sp_model_kwargs": {}, "separate_vocabs": false, "special_tokens_map_file": null, "name_or_path": "marian-models/opusTCv20210807_transformer-big_2022-08-10/zls-itc", "tokenizer_class": "MarianTokenizer"}